MCP Agent Builder & Tester

Follow these proven practices to create effective agent prompts that deliver consistent, high-quality results.

Few-shot prompts help set the right expectations for format and tone. Adding edge cases can help—just watch out for overfitting.

Clear, concise, verb-driven prompts usually perform best. Less ambiguity = better results.

Be explicit about structure, style, and length. For example, say "Give a 3-sentence summary in bullet points."

Tell the model what to do rather than what not to do, unless you're enforcing strict safety rules.

Add placeholders (like names, dates) to make prompts reusable and dynamic.

Tables, lists, and schemas like JSON can guide the model's focus in useful ways.

Every model version responds differently. What worked for GPT-3.5 might not work the same with GPT-4.

Formats like JSON or CSV are easier to parse and often reduce follow-up cleanup.

Collaborating on prompts makes the process more efficient and helps uncover better patterns.

Keep CoT prompts simple ("Let's think step by step…"). Don't overuse it on reasoning-native models.

Log versions, results, and tweaks so you don't lose progress or repeat mistakes.